Fractionating column

Summary

A fractionating column or fractional column is equipment used in the distillation of liquid mixtures to separate the mixture into its component parts, or fractions, based on the differences in volatilities. Fractionating columns are used in small-scale laboratory distillations as well as large-scale industrial distillations. Laboratory fractionating columns A laboratory fractionating column is a piece of glassware used to separate vaporized mixtures of liquid compounds with close volatility. Most commonly used is either a Vigreux column or a straight column packed with glass beads or metal pieces such as Raschig rings. Fractionating columns help to separate the mixture by allowing the mixed vapors to cool, condense, and vaporize again in accordance with Raoult's law. With each condensation-vaporization cycle, the vapors are enriched in a certain component. A larger surface area allows more cycles, improving separation. This is the rationale for a Vigreux column or a packed

Official source

https://en.wikipedia.org/wiki/Fractionating_column

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On reducing the number of decision variables for dynamic optimization

Dominique Bonvin, Diogo Filipe Mateus Rodrigues

This paper presents an input parameterization for dynamic optimization that allows reducing the number of decision variables compared to traditional direct methods. A small number of decision variables is likely to be beneficial for various applications such as global optimization and real-time optimization in the presence of plant-model mismatch. The procedure consists of three steps: (i) adjoint-free optimal control laws are computed for all arc types that may be present in the solution, and a finite set of plausible arc sequences is postulated; (ii) the sensitivity-seeking arcs are either described by analytical control laws or approximated by cubic splines, which results in a parsimonious input parameterization that represents the optimal inputs using only a few parameters, namely, switching times and initial conditions for the sensitivity-seeking arcs; and (iii) for each arc sequence, optimal parameter values are computed via numerical optimization, and the sequence with the best cost is optimal. The procedure is illustrated via the simulated examples of a semibatch reactor and a distillation column.

2019

Modelling the fate of chromated copper arsenate in a sandy soil

David Andrew Barry

A pulse of chromated copper arsenate (CCA, a timber preservative) was applied in irrigation water to an undisturbed field soil in a laboratory column. Concentrations of various elements in the leachate from the column were measured during the experiment. Also, the remnants within the soil were measured at the end of the experiment. The geochemical modelling package, PHREEQC-2, was used to simulate the experimental data. Processes included in the CCA transport modelling were advection, dispersion, non-specific adsorption (cation exchange) and specific adsorption by clay minerals and organic matter, as well as other possible chemical reactions such as precipitation/dissolution. The modelling effort highlighted the possible complexities in CCA transport and reaction experiments. For example, the uneven dosing of CCA as well as incomplete knowledge of the soil properties resulted in simulations that gave only partial, although reasonable, agreement with the experimental data. Both the experimental data and simulations show that As and Cu are strongly adsorbed and therefore, will mostly remain at the top of the soil profile, with a small proportion appearing in leachate. On the other hand, Cr is more mobile and thus it is present in the soil column leachate. Further simulations show that both the quantity of CCA added to the soil and the pH of the irrigation water will influence CCA transport. Simulations suggest that application of larger doses of CCA to the soil will result in higher leachate concentrations, especially for Cu and As. Irrigation water with a lower pH will dramatically increase leaching of Cu. These results indicate that acidic rainfall or significant accidental spillage of CCA will increase the risk of groundwater pollution.

2004

This paper proposes a new point of view in analyzing the optimal Gibbs energy dissipation in growing microorganisms. Small Gibbs energy dissipation in growth would be of biological advantage because less resource is consumed and the biomass yield on these resources could be maximized. It is however not so clear why microorganisms still dissipate considerable amounts of Gibbs energy while growing. Distillation columns are used as a simple qualitative model system in order to gain a qualitative understanding of the question. In both growing microorganisms and continuously operated distillation columns, small energy dissipation values result in small process driving forces and therefore in tentatively slow operation. In microorganisms this entails relatively higher maintenance energy requirements, increasing thereby the resource cost for growth and decreasing the biomass yield. In distillation columns, it results in higher capital and maintenance cost, thereby increasing overall process costs. A simple model is proposed to calculate the biomass yield as a function of Gibbs energy dissipation. It shows that this function goes through a maximum because of maintenance requirements at small dissipations. Experimental data confirm that growing microorganisms dissipate an amount of Gibbs energy that is associated with this maximum.

De Gruyter2014